Search Results for "post"
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Showing 61 open source projects for "post"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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1
KaTrain
Improve your Baduk skills by training with KataGo
...The application allows users to play against AI opponents with adjustable difficulty, including intentionally weakened versions of the engine that simulate human-like play styles. One of its key strengths is its ability to generate detailed post-game analyses, highlighting the moves that resulted in the greatest loss of points and suggesting improvements. KaTrain also includes interactive learning features such as retrying moves, exploring variations, and visualizing territory control probabilities. -
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Depth Anything 3
Recovering the Visual Space from Any Views
...The model can be applied to photography, AR/VR content creation, robotics perception, and 3D reconstruction workflows, making it versatile across industries and research domains. It includes support for high-resolution inputs and post-processing tools that refine depth predictions, helping downstream tasks like segmentation, bounding volume estimation, and mixed reality layering. -
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Agent Behavior Monitoring
The open source post-building layer for agents
...Judgeval transforms agent interaction trajectories into structured evaluation datasets that can be used for reinforcement learning, supervised fine-tuning, or other forms of post-training improvement. The framework includes tools that analyze agent behavior patterns and group interaction trajectories by behavior type or topic, allowing researchers to detect weaknesses or unexpected behaviors. -
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KServe
Standardized Serverless ML Inference Platform on Kubernetes
...It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary Rollouts to your ML deployments. It enables a simple, pluggable, and complete story for Production ML Serving including prediction, pre-processing, post-processing and explainability. KServe is being used across various organizations. -
Compliant and Reliable File Transfers Backed by Top Security CertificationsStop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
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Cheat on Content
Workflow that turns every post into a calibrated experiment
Cheat on Content is an AI-assisted workflow for creators who want to make content performance measurable instead of relying on instinct alone. It turns every post into a structured experiment by asking creators to score ideas, make blind predictions, publish, review results after a defined time window, and evolve their own content rubric. Rather than generating posts for the creator, it focuses on sharpening judgment and helping users understand why certain content performs better. The project is built around the loop of score, predict, publish, retro, and improve. ... -
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DeepSeek-OCR
Contexts Optical Compression
...It supports local deployment, enabling organizations concerned about privacy or latency to run the pipeline on-premises rather than send sensitive documents to third-party cloud services. The codebase is written in Python with a focus on modularity: you can swap preprocessing, recognition, and post-processing components as needed for custom workflows. -
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slime LLM
slime is an LLM post-training framework for RL Scaling
slime is an open-source large language model (LLM) post-training framework developed to support reinforcement learning (RL)-based scaling and high-performance training workflows for advanced LLMs, blending training and rollout modules into an extensible system. It offers a flexible architecture that connects high-throughput training (e.g., via Megatron-LM) with a customizable data generation pipeline, enabling researchers and engineers to iterate on new RL training paradigms effectively. ... -
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Dream Textures
Stable Diffusion built-in to Blender
...Inpaint to fix up images and convert existing textures into seamless ones automatically. Outpaint to increase the size of an image by extending it in any direction. Perform style transfer and create novel animations with Stable Diffusion as a post processing step. Dream Textures has been tested with CUDA and Apple Silicon GPUs. Over 4GB of VRAM is recommended. -
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NannyML
Detecting silent model failure. NannyML estimates performance
...NannyML closes the loop with performance monitoring and post deployment data science, empowering data scientist to quickly understand and automatically detect silent model failure. By using NannyML, data scientists can finally maintain complete visibility and trust in their deployed machine learning models. When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance. -
AI Agents That Actually Do the WorkClickUp's Super Agents run 24/7 inside your workspace: triaging bugs, drafting content, updating statuses, and routing tasks without being told twice. Connect them to 500+ tools and let them execute, not just suggest. Build custom agents in minutes that understand your workflows and act on them autonomously.
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RSS to Telegram Bot
A Telegram RSS bot that cares about your reading experience
A Telegram RSS bot that cares about your reading experience. -
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Claude-Flow
The leading agent orchestration platform for Claude
...At its core, Claude-Flow integrates Dynamic Agent Architecture (DAA) for self-organizing agent management, neural pattern recognition accelerated by WebAssembly SIMD, and a SQLite-based memory system for context retention and knowledge persistence across tasks. It automates development workflows via pre- and post-operation hooks, providing seamless coordination, code formatting, validation, and performance optimization. -
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Desloppify
Agent harness to make your slop code well-engineered and beautiful
...This makes it especially useful in workflows where AI-generated text needs to be refined before publication or use in production. It may also support integration into pipelines, allowing automatic post-processing of outputs. The project reflects a growing need to manage and optimize AI-generated content rather than simply produce it. Overall, desloppify acts as a refinement layer that enhances clarity and usability of textual outputs. -
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Sygil WebUI
Stable Diffusion web UI
Post-processing and enhancement are a major emphasis: the interface can route images through different upscalers and face-enhancement tools, helping users turn raw generations into cleaner, higher-resolution results. -
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NVIDIA Isaac GR00T
NVIDIA Isaac GR00T N1.5 is the world's first open foundation model
...It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. The vision-language model remains frozen during both pretraining and finetuning, preserving language understanding and improving generalization. Streamlined MLP connection between vision encoder and LLM with added layer normalization. -
15
Heretic
Fully automatic censorship removal for language models
Heretic is an open-source Python tool that automatically removes the built-in censorship or “safety alignment” from transformer-based language models so they respond to a broader range of prompts with fewer refusals. It works by applying directional ablation techniques and a parameter optimization strategy to adjust internal model behaviors without expensive post-training or altering the core capabilities. Designed for researchers and advanced users, Heretic makes it possible to study and experiment with uncensored model responses in a reproducible, automated way. The project can decensor many popular dense and some mixture-of-experts (MoE) models, supporting workflows that would otherwise require manual tuning. ... -
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Triton Inference Server
The Triton Inference Server provides an optimized cloud
...Triton delivers optimized performance for many query types, including real-time, batched, ensembles, and audio/video streaming. Provides Backend API that allows adding custom backends and pre/post-processing operations. Model pipelines using Ensembling or Business Logic Scripting (BLS). HTTP/REST and GRPC inference protocols based on the community-developed KServe protocol. A C API and Java API allow Triton to link directly into your application for edge and other in-process use cases. -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The GLM-Z1-32B-0414 line adds deeper mathematical, coding, and logical reasoning via extended reinforcement learning and pairwise ranking feedback, while GLM-Z1-Rumination-32B-0414 introduces a “rumination” mode that performs longer, tool-using deep research for complex, open-ended tasks. ... -
18
pycm
Multi-class confusion matrix library in Python
PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers. -
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Depth Pro
Sharp Monocular Metric Depth in Less Than a Second
Depth Pro is a foundation model for zero-shot metric monocular depth estimation, producing sharp, high-frequency depth maps with absolute scale from a single image. Unlike many prior approaches, it does not require camera intrinsics or extra metadata, yet still outputs metric depth suitable for downstream 3D tasks. Apple highlights both accuracy and speed: the model can synthesize a ~2.25-megapixel depth map in around 0.3 seconds on a standard GPU, enabling near real-time applications. The... -
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ERNIE
The official repository for ERNIE 4.5 and ERNIEKit
ERNIE is an open-source large-model toolkit and model family from the PaddlePaddle ecosystem that focuses on training, fine-tuning, compression, and practical application of ERNIE large language models. The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment. It supports both full-parameter training and parameter-efficient approaches so teams can choose... -
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MaxText
A simple, performant and scalable Jax LLM
MaxText is a high-performance, highly scalable open-source framework designed to train and fine-tune large language models using the JAX ecosystem. The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small... -
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LLM-Aided OCR Project
Enhances Tesseract OCR output using LLMs (local or API)
LLM Aided OCR is an open-source system designed to improve optical character recognition accuracy by combining traditional OCR tools with large language models. The project addresses common OCR challenges such as distorted text, unusual fonts, historical documents, and complex layouts that often produce inaccurate results with standard OCR pipelines. The system first extracts raw text using OCR engines and then applies language models to analyze and correct recognition errors based on... -
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PentestAgent
AI agent framework for black-box security testing
...It brings a modular and automated approach to penetration testing by orchestrating a suite of tools and scripts that can emulate common exploitation techniques, reconnaissance workflows, and post-exploitation activities across targets. Users configure rules, policies, and environments, and the agent continuously probes for weaknesses, prioritizes findings, and generates contextual reports that help both technical and non-technical stakeholders understand risk exposure. Because it supports a range of plug-ins and external security tools, pentestagent can be adapted for web applications, network infrastructure, API surfaces, and even cloud environments, making it flexible for diverse security programs. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training... -
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BlogWizard
Generate blog articles from video or audio
BlogWizard is a demo/utility project built on top of Groq’s LLM infrastructure that converts video or audio content into well-structured blog posts, enabling creators to repurpose multimedia content into text — useful for SEO, accessibility, or reaching audiences that prefer reading. The tool uses transcription (e.g. via Whisper) to extract text from audio/video, then runs an LLM-based generation pipeline to transform that content into coherent, readable blog-format posts — with sections,...
